Energy is provided by suppliers to consumers in many forms and from many sources. Typical forms and sources of energy include electricity, natural gas, coal, oil, atomic energy etc.
Escalating energy costs and infrastructure costs have made managing both energy supply and energy consumption a critical issue which is important to both suppliers of energy and consumers of energy.
From a supplier's perspective, both the energy consumption of consumers and the energy demand by consumers must be accommodated by the energy infrastructure. Energy consumption is the total amount of energy which is consumed over a time period, while energy demand is the rate at which the energy is consumed. Peak energy demand is the maximum rate at which energy is consumed. Energy consumption over a time period is a function of the energy demand over the time period.
An energy infrastructure must be capable of supplying the total amount of energy that is required by consumers and must also be capable of satisfying the peak demand for energy which is imposed upon the energy infrastructure.
In a typical energy supply system, the energy demand fluctuates over minutes, hours, days, weeks, months etc. Since energy consumption is a function of energy demand, an energy supply system in which energy consumption is relatively low may exhibit a relatively high peak energy demand if the energy demand fluctuates greatly, while an energy supply system in which energy consumption is relatively high may exhibit a relatively low peak energy demand if the energy demand fluctuates minimally.
An efficient energy supply system is a system in which the energy demand fluctuates minimally, since the energy infrastructure must be designed to satisfy the peak demand. As the fluctuation of the energy demand decreases, the peak energy demand for the energy supply system approaches the average energy demand on the energy supply system, which is the lowest peak energy demand which can be attained for the energy supply system. The energy demand on an energy supply system is therefore preferably managed so that the peak energy demand is minimized.
An energy supply system may provide energy to any number of consumers. The energy demand on an energy supply system may be managed on one level by managing the energy demands of the consumers who are connected with the energy supply system. The energy demand on an energy supply system may also be managed on a second level by managing the energy demands of the individual energy consuming loads which are connected with the energy supply system through the consumers.
In either case, managing the energy demand on the energy supply system involves distributing the energy demands of consumers and/or loads in order to avoid a large peak energy demand on the energy supply system. The distribution of energy demands may be accomplished by adjusting the times at which “discretionary loads” consume energy from the energy supply system.
A discretionary load is an energy consuming load which is not required to be operated rigidly according to a fixed schedule, or rigidly according to a fixed set of constraints such as temperature, humidity, etc., with the result that the time or times at which it consumes energy can be adjusted. Typically, a discretionary load has a duty cycle which is less than 100 percent, where duty cycle is defined as the percentage of time that the load must operate in order to satisfy its assigned objectives.
For example, if a heater must operate 50 percent of the time in order to maintain a desired temperature within a space, the duty cycle for the heater is 50 percent. If the heater isn't required to operate rigidly according to a fixed schedule, or rigidly within a fixed set of constraints while satisfying its duty cycle, the heater is also a discretionary load.
Some energy suppliers provide incentives or disincentives to consumers to assist in managing the energy demand on the energy supply system.
For example, in the case of an electrical system, suppliers may include in their billing both a “consumption charge” and a “peak demand charge”, particularly in the case of commercial, institutional and industrial consumers. The consumption charge is based upon the total amount of electricity consumed in the billing period (typically measured in kilowatt-hours, or “kWh”). The peak demand charge is often based upon the greatest amount of electricity used during a sustained fifteen minute period (typically measured in kilowatts, or “kW”).
The consumption charge compensates the supplier for the electricity which is consumed by a consumer. The peak demand charge compensates the supplier for the energy infrastructure which must be provided in order to accommodate the peak demand on the electrical system.
It may therefore be in the financial interest of a consumer to manage its energy demand in order to minimize the peak energy demand which is imposed by the consumer on the energy supply system.
Systems have been contemplated for managing energy consumption and/or energy demand.
U.S. Pat. No. 4,023,043 (Stevenson) describes a system and method for lowering electrical energy peak demand while minimizing service disruption, which includes a centralized transmitter means which generates and transmits signals which disconnect interruptible loads in response to the approach of an excessive demand peak, and which generates and transmits signals to reconnect the interruptible loads thereafter, based upon characteristic projected energy consumption profiles predicted from past historical records.
U.S. Pat. No. 4,264,960 (Gurr) describes a system for permitting an electric power utility to control the distribution of its power along its power lines from a substation to a plurality of customer loads. The system provides direct control of customer loads with a view toward facilitating enablement of a load management philosophy which includes peak shaving and load deferral. The system includes a master control station which generates master control signals which are converted to pulse code signals by a substation injection unit, wherein the pulse code signals provide instructions for connecting or disconnecting customer loads from the power lines.
U.S. Pat. No. 4,686,630 (Marsland et al) describes a load management control system and method which communicates load shedding information from a central station controller to a substation controller. The substation controller then sends encoded step voltage signals down a power distribution line to a load control receiver, which decodes the signals and controls loads which are associated with the load control receiver.
U.S. Pat. No. 5,244,146 (Jefferson et al) describes an apparatus and method for controlling the operation of an HVAC system in order to conserve energy. The method involves initiating a “fuel-on interval” in which fuel is consumed by the HVAC system, terminating the fuel-on interval and initiating a “fuel-off interval” in which fuel is not consumed by the HVAC system. H-eat is distributed through the HVAC system during a “delivery interval” which is initiated during the fuel-off interval. The apparatus includes a thermostat which initiates and terminates the fuel-on interval, the fuel-off interval, and the delivery interval.
European Patent Specification No. EP 0 814 393 B1 (Eriksson et al) describes a system for controlling and supervising electrical components/devices connected to an electrical network via a public information network, wherein the system is accessible from any terminal connected to the public information network.
U.S. Patent Application Publication No. US 2002/0162032 A1 (Gundersen et al) describes a system, method and computer program for providing automated load management in an electrical power generation, transmission and distribution network by means of control signals in a communications protocol which is compatible with the world wide web and other Internet technologies. The method involves the carrying out by a load point device of load shaving or load shedding actions affecting loads, which actions are based upon decisions calculated using reference information for the loads which are stored in the device.
U.S. Patent Application Publication No. US 2005/0192713 A1 (Weik et al) describes a method of managing energy consumption by a group of energy consuming devices. The energy consuming devices exchange messages according to an energy management control protocol via a communication media. The energy management control protocol includes an energy booking message type for announcing future energy consumption, an energy reduction indication type for announcing possible reduction of energy consumption, and a granting message type for granting an energy booking message and/or an energy reduction indication. The energy consuming devices negotiate their energy consumption by means of the messages exchanged according to the energy management control protocol and control their energy consumption according to the result of this negotiation. The group of energy consuming devices are described as constituting a self-organizing network which negotiate with each other according to scheduling rules without a central energy management control device to provide scheduling functionalities.
Self-organization as referred to in Weik et al is somewhat related to multi-agent systems and emergence theory. Self organization is a process in which the internal organization of a system increases in complexity without guidance or management from an outside source. A multi-agent system is a system composed of a group of agents which interact according to defined rules to achieve functionality that would be difficult or impossible to achieve by the agents acting individually. Emergence is the process of complex pattern formation from simple rules.
Emergence is sometimes described with reference to “swarm” or “hive” behaviour whereby a group of simple devices, acting in a swarm, can exhibit behaviour which is seemingly more intelligent and complex than the simple behaviour programmed into the individual devices.
Both multi-agent systems and emergence theory have been proposed for use in controlling complex environments.
Brazier, Frances M. T., Cornelissen, Frank, Gustavsson, Rune, Jonker, Catholijn M., Lindeberg, Olle, Polak, Bianca and Treur, Jan, “A Multi-Agent System Performing One-To-Many Negotiation for Load Balancing of Electricity Use”, Electronic Commerce Research And Applications, 1 (2002) 208-224 describes a prototype system which involves interaction between a Utility Agent (i.e., a utility supplier) and a group of Customer Agents (i.e., consumers) for the purpose of negotiating for the supply of electricity from the Utility Agent to the Customer Agents.
Van Dyke Parunak, H., “An Emergent Approach to Systems of Physical Agents”, J. Expt. Theor. Artif Intell. 9 (1997)211-213 describes an application of emergence theory in which “agents” (such as parts and equipment) interact with each other in order to permit an overall shop schedule to emerge dynamically from the interaction, instead of being imposed top-down from a central control.
Rosario, L. C., “Multi-Agent Load Power Segregation for Electric Vehicles”, 2005 IEEE Vehicle Power and Propulsion Conference (IEEE Cat. No. 05EX1117C), 2006, p 6 pp. describes the prioritization of activation of agents, wherein the agents are comprised of non-propulsion loads which have been segregated into multi-priority, multi-time constant electrical burdens which may be imposed on an onboard energy storage system in an electric vehicle. The prioritization is performed using an algorithm which ensures the availability of the propulsion load demand by arbitrating the activation of the non-propulsion agents based upon assigned priority levels. This paper is described as providing an initial step toward ongoing investigations into agent based power and energy management schemes.
Valckenaers, P. “On the Design of Emergent Systems: An Investigation of Integration and Interoperability Issues”, Engineering Applications of Artificial Intelligence, v. 16, n. 4, Jun. 2003, p. 377-93 discusses design principles for the design of components for emergent systems, based upon experience gained during the development of research prototypes for multiagent manufacturing control systems.
Ward, J., “Sensor Networks for Agent Based Distributed Energy Resources”, The Second IEEE Workshop on Embedded Networked Sensors (IEEE Cat. No. 05EX1105), 2005, p. 159-60 describes the development of agents for the control of distributed energy resources (DERs) in an electricity network, which resources include both generators and loads. The agents may be used to allow collaboration amongst DERs in order to generate an aggregated response by the DERs to support the electricity network at times of peak demand.
Fischer, K., “Specialised Agent Applications”, Multi-Agent Systems and Applications, 9th ECCAI Advanced Course, ACAI 2001 and Agent Link's 3rd European Agent Systems Summer Scholl, EASSS 2001, Selected Tutorial Papers (Lecture Notes in Computer Science Vol. 2086), 2001, p. 365-82 provides an overview of multi-agent system applications, focusing on the application of multi-agent systems in the context of supply chain management in virtual enterprises.
There remains a need for a method and/or system for managing a group of energy consuming loads and/or an energy consuming load in the group of energy consuming loads which is relatively simple, which does not require negotiation amongst the loads, and which may be used either with or without centralized control of the loads.
There remains a need for such a method and/or system for use in managing the energy demands of the loads and the collective energy demand of the group of loads with the goal of controlling the peak energy demand which is exhibited by the group of loads.
There remains a need for such a method and/or system in which each of the loads is controlled using relatively simple rules which are applicable to each of the loads.